






"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


snake_case : Any     		=		logging.get_logger(__name__)  # pylint: disable=invalid-name



class        UpperCamelCase__ (				a_):







    """simple docstring"""







    def __init__(		self :	str				,    UpperCamelCase_ :	Any				,    UpperCamelCase_ :	Optional[Any]=7_6_8 ):





           '''simple docstring'''

           super().__init__(UpperCamelCase_ )
           __magic_name__      				=    proj_size

           __magic_name__      				=    CLIPVisionModel(UpperCamelCase_ )
           __magic_name__      				=    PaintByExampleMapper(UpperCamelCase_ )
           __magic_name__      				=    nn.LayerNorm(config.hidden_size )
           __magic_name__      				=    nn.Linear(config.hidden_size				,    self.proj_size )

           # uncondition for scaling
           __magic_name__      				=    nn.Parameter(torch.randn((1, 1, self.proj_size) ) )







    def 				a__			(		self :	Union[str, Any]				,    UpperCamelCase_ :	Union[str, Any]				,    UpperCamelCase_ :	Any=False ):





           '''simple docstring'''

           __magic_name__      				=    self.model(pixel_values=UpperCamelCase_ )
           __magic_name__      				=    clip_output.pooler_output
           __magic_name__      				=    self.mapper(latent_states[:, None] )
           __magic_name__      				=    self.final_layer_norm(UpperCamelCase_ )
           __magic_name__      				=    self.proj_out(UpperCamelCase_ )
           if return_uncond_vector:
                  return latent_states, self.uncond_vector

           return latent_states



class        UpperCamelCase__ (				nn.Module):







    """simple docstring"""







    def __init__(		self :	Tuple				,    UpperCamelCase_ :	int ):





           '''simple docstring'''

           super().__init__()
           __magic_name__      				=    (config.num_hidden_layers + 1) // 5
           __magic_name__      				=    config.hidden_size
           __magic_name__      				=    1
           __magic_name__      				=    nn.ModuleList(
               [
                   BasicTransformerBlock(UpperCamelCase_				,    UpperCamelCase_				,    UpperCamelCase_				,    activation_fn='gelu'				,    attention_bias=UpperCamelCase_ )
                   for _ in range(UpperCamelCase_ )
               ] )







    def 				a__			(		self :	List[str]				,    UpperCamelCase_ :	Any ):





           '''simple docstring'''

           for block in self.blocks:
                  __magic_name__      				=    block(UpperCamelCase_ )

           return hidden_states







"""simple docstring"""
def 							A						(				__snake_case: int = 3 ,     __snake_case: int = 7 ,     __snake_case: int = 1_0_0_0_0_0_0  )    ->		int:

       """simple docstring"""





       __magic_name__      				=    0
       __magic_name__      				=    1

       for current_denominator in range(1 ,     limit + 1  ):
              __magic_name__      				=    current_denominator * numerator // denominator
              if current_denominator % denominator == 0:
                     current_numerator -= 1
              if current_numerator * max_denominator > current_denominator * max_numerator:
                     __magic_name__      				=    current_numerator
                     __magic_name__      				=    current_denominator
       return max_numerator


if __name__ == "__main__":
 print(solution(numerator=3, denominator=7, limit=1_0_0_0_0_0_0))